class_docstr: Synaptic Intelligence plugin.
  
  This is the Synaptic Intelligence PyTorch implementation of the
  algorithm described in the paper
  "Continuous Learning in Single-Incremental-Task Scenarios"
  (https://arxiv.org/abs/1806.08568)
  
  The original implementation has been proposed in the paper
  "Continual Learning Through Synaptic Intelligence"
  (https://arxiv.org/abs/1703.04200).
  
  This plugin can be attached to existing strategies to achieve a
  regularization effect.
  
  This plugin will require the strategy `loss` field to be set before the
  `before_backward` callback is invoked. The loss Tensor will be updated to
  achieve the S.I. regularization effect.
code: def not_excluded_parameters(
      model: Module, excluded_parameters: Set[str]
  ) -> Sequence[Tuple[str, Tensor]]:
      # Add wildcards ".*" to all excluded parameter names
      result: List[Tuple[str, Tensor]] = []
      excluded_parameters = (
          SynapticIntelligencePlugin.explode_excluded_parameters(
              excluded_parameters
          )
      )
      layers_params = get_layers_and_params(model)
  
      for lp in layers_params:
          if isinstance(lp.layer, _NormBase):
              # Exclude batch norm parameters
              excluded_parameters.add(lp.parameter_name)
  
      for name, param in model.named_parameters():
          accepted = True
          for exclusion_pattern in excluded_parameters:
              if fnmatch(name, exclusion_pattern):
                  accepted = False
                  break
  
          if accepted:
              result.append((name, param))
  
      return result
  
imports: from fnmatch import fnmatch
  from typing import Optional, Sequence, Any, Set, List, Tuple, Dict, Union, TYPE_CHECKING
  import numpy
  import torch
  from torch import Tensor
  from torch.nn import Module
  from torch.nn.modules.batchnorm import _NormBase
  from .ewc import EwcDataType, ParamDict
  from avalanche.training.plugins.strategy_plugin import SupervisedPlugin
  from avalanche.training.utils import get_layers_and_params, ParamData
label_desc: Use image node_id 17 for calling the SynapticIntelligencePlugin obj's underlying member method code with example usage: obj.not_excluded_parameters(model, excluded_parameters) and returns: result